I recently posted on how to find the distribution of functions of random variables, i.e., the distribution of $Y=g(X)$, where $X$ is a random variable with known distribution and $y=g(x)$ is some function. As a natural extension of this concept we may ask ourselves what happens if we have two random variables involved. Let […]
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Widely linear systems of equations
I would strongly assume that this must exist already somewhere but I couldn’t find the solution so I thought it would be interesting to post it here. The closest to this I could find is widely linear estimation (e.g., Picinbono, TSP, 1995), but it’s not quite the same. Consider the following widely linear system of […]
… and a simpler proof for it
A much simpler proof for the more generic algebraic rule on manipulating quadratic forms I posted recently just became apparent to me. All you need to do is to first show that $${\rm trace}\{\ma{A}^{\rm H} \cdot \ma{B}\} = {\rm vec}\{\ma{A}\}^{\rm H} \cdot {\rm vec}\{\ma{B}\},$$ which is fairly easy because both represent a short-hand notation for […]
Even more algebra fun
I just realized that there is an even more general version of the rules for quadratic forms I posted recently: $${\rm trace}\left(\ma{A} \cdot \ma{X} \cdot \ma{R} \cdot \ma{X}^{\rm H} \cdot \ma{B}^{\rm H}\right) = {\rm vec}\left(\ma{X}\right)^{\rm H} \cdot \left( \ma{R}^{\rm T} \otimes \ma{B}^{\rm H} \cdot \ma{A} \right) \cdot {\rm vec}\left(\ma{X}\right) $$ Enjoy!
Fun with statistics – transformations of random variables part 1
Here is another tool I learned about and have found very useful ever since then: transformations of random variables. The basic idea is this: Given a random variable $X$ from which we know how it is distributed, i.e., either its probability density function (PDF) $f_X(x)$ or its cumulative distribution function (CDF) $F_X(x)$, find the distribution […]